Forecasting Mutual Fund Performance Under Market Scenarios: A Regression-Based Sensitivity Analysis of Nippon India Large Cap Fund and Nifty 500

This paper proposes and tests an integrated forecasting model for predicting the trajectory of the mutual fund Net Asset Value (NAV) using regression-based transmission mechanisms as the backbone. Based on 156 monthly observations from January 2013 to December 2025, the study investigates the empirical link between the Nifty 500 index of the national stock exchange and the Nippon India Large Cap Fund (NILK) which is one of the most well-known equity funds in India that follows a large-cap strategy. The ordinary least squares (OLS) regression model shows an excellent explanatory power (R2 = 0.936) and the estimated transmission coefficient (β = 0.916) indicates that 93.6% of fund NAV variations can be attributed to variations of the benchmark index. The base case returns to funds over 12 months are 9.41%, the optimistic case returns are 77.19%, and the recessionary case returns are a negative −32.44%—a combined range of 109.6 percentage points and strong scenario discrimination. The ratios of upside capture (86.1%) and downside capture (96.0%) indicate an asymmetric risk-return profile with the fund sacrificing a disproportionate amount of upside participation compared to downside protection. The worst-case analysis of maximum drawdown is nearly identical to the drawdown of the benchmark, which bottomed at 33.79%, while it measures a 32.44% drawdown, indicating that the asset class may offer some protection from downside risk. The results are robust through subsample stability tests and alternative scenarios and beta sensitivity analyses. The findings have immediate relevance to individual investors, financial advisors and fund managers in the evolving retail investment landscape in India.